{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T21:21:18Z","timestamp":1777929678991,"version":"3.51.4"},"reference-count":12,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2016,7,11]],"date-time":"2016-07-11T00:00:00Z","timestamp":1468195200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Stat Methods Med Res"],"published-print":{"date-parts":[[2016,8]]},"abstract":"<jats:p>Although there is considerable interest in adverse events observed in clinical trials, projecting adverse event incidence rates in an extended period can be of interest when the trial duration is limited compared to clinical practice. A na\u00efve method for making projections might involve modeling the observed rates into the future for each adverse event. However, such an approach overlooks the information that can be borrowed across all the adverse event data. We propose a method that weights each projection using a shrinkage factor; the adverse event-specific shrinkage is a probability, based on empirical Bayes methodology, estimated from all the adverse event data, reflecting evidence in support of the null or non-null hypotheses. Also proposed is a technique to estimate the proportion of true nulls, called the common area under the density curves, which is a critical step in arriving at the shrinkage factor. The performance of the method is evaluated by projecting from interim data and then comparing the projected results with observed results. The method is illustrated on two data sets.<\/jats:p>","DOI":"10.1177\/0962280213483499","type":"journal-article","created":{"date-parts":[[2013,4,16]],"date-time":"2013-04-16T22:30:32Z","timestamp":1366151432000},"page":"1381-1392","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Projecting adverse event incidence rates using empirical Bayes methodology"],"prefix":"10.1177","volume":"25","author":[{"given":"Guoguang (Julie)","family":"Ma","sequence":"first","affiliation":[{"name":"Gilead Sciences, 333 Lakeside Drive, Foster City, California, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jitendra","family":"Ganju","sequence":"additional","affiliation":[{"name":"Gilead Sciences, 333 Lakeside Drive, Foster City, California, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Huang","sequence":"additional","affiliation":[{"name":"Amgen Inc., 1150 Veterans Blvd., South San Francisco, California, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2016,7,11]]},"reference":[{"key":"bibr1-0962280213483499","doi-asserted-by":"publisher","DOI":"10.1177\/1740774509344101"},{"key":"bibr2-0962280213483499","doi-asserted-by":"publisher","DOI":"10.1191\/0962280204sm363ra"},{"key":"bibr3-0962280213483499","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1995.tb02031.x"},{"key":"bibr4-0962280213483499","doi-asserted-by":"publisher","DOI":"10.1111\/j.0006-341X.2004.00186.x"},{"key":"bibr5-0962280213483499","doi-asserted-by":"crossref","first-page":"1006","DOI":"10.1080\/10543406.2010.520181","volume":"21","author":"Xia AH","year":"2011","journal-title":"J Biopharm Stat"},{"key":"bibr6-0962280213483499","doi-asserted-by":"publisher","DOI":"10.1111\/1467-9868.00346"},{"key":"bibr7-0962280213483499","doi-asserted-by":"publisher","DOI":"10.1198\/016214501753382129"},{"key":"bibr8-0962280213483499","doi-asserted-by":"publisher","DOI":"10.1002\/gepi.1124"},{"key":"bibr9-0962280213483499","doi-asserted-by":"publisher","DOI":"10.1198\/016214504000000089"},{"key":"bibr10-0962280213483499","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/69.3.493"},{"key":"bibr11-0962280213483499","doi-asserted-by":"crossref","first-page":"1683","DOI":"10.1093\/genetics\/157.4.1683","volume":"157","author":"Mosig MO","year":"2001","journal-title":"Genetics"},{"key":"bibr12-0962280213483499","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-9473(01)00046-9"}],"container-title":["Statistical Methods in Medical Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/0962280213483499","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/0962280213483499","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/0962280213483499","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T23:46:28Z","timestamp":1777679188000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/0962280213483499"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,7,11]]},"references-count":12,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2016,8]]}},"alternative-id":["10.1177\/0962280213483499"],"URL":"https:\/\/doi.org\/10.1177\/0962280213483499","relation":{},"ISSN":["0962-2802","1477-0334"],"issn-type":[{"value":"0962-2802","type":"print"},{"value":"1477-0334","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,7,11]]}}}